## Introduction — Renminbi in Global Payments (wpiea2023077-print-pdf)

## Source details

**Canonical URL:** [Introduction — Renminbi in Global Payments (wpiea2023077-print-pdf)](https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023077-print-pdf.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/wp/2023/english/wpiea2023077-print-pdf.pdf.md)
- [Structured JSON version](/-/media/files/publications/wp/2023/english/wpiea2023077-print-pdf.pdf.json)

---

### Overview: China’s financial integration and RMB internationalization
- China "accounts for one-third of global growth (IMF, 2018)."
- China’s international assets and liabilities: 4 percent of world external assets and liabilities; China’s share in global trade: 13 percent.
- International use of RMB:
  - 2 percent of all global cross-border payments (SWIFT data).
  - 3 percent of central bank reserve assets (IMF COFER dataset).
- Capital account: China has maintained a closed capital account with strong capital account limits; capital mobility control tighter than many peers.

### Timeline and payment infrastructure
- PBC policy milestones and infrastructure:
  - 2009: PBC permitted cross-border settlements in RMB (pilots; nationwide since 2011).
  - 2015: RMB joined the basket of Special Drawing Rights.
  - Since 2017: Financial liberalization accelerated; RMB bonds included in major global indices.
  - Offshore clearing banks established beginning in 2003 (first in Hong Kong SAR).
  - CIPS: first phase completed in 2015; second phase completed in 2018. CIPS membership to date: 77 direct participants and 1283 indirect participants.

### Regional patterns and stylized facts (SWIFT-based)
- Sample: SWIFT transaction currency usage covering 125 economies (data back to 2010).
- Evolution of RMB share in an economy’s total payments with China:
  - Median RMB usage: around 0 in 2014 → 20 percent in 2021.
  - 75th percentile: 0 in 2014 → 70 percent in 2021.
  - 25th percentile: close to zero in 2021.
- Geographic concentration (2021): RMB uptake pronounced in Asian countries (e.g., Mongolia, Laos), emerging markets (e.g., Chile, Turkey, Argentina), and in countries subject to U.S. dollar sanctions (e.g., Iran).

### Policy instruments to facilitate RMB use
- Bilateral swap lines (PBC):
  - As of 2022: 38 bilateral swap lines outstanding, amounting to around 4 trillion RMB.
  - Typical term: three years, often renewed; some swap lines scaled up (e.g., Hong Kong SAR, Singapore, South Korea).
  - Activation has been limited: a 2015 report indicated about 100 billion of the 3 trillion RMB outstanding swaps were used in that year (less than 1 percent).
  - Function: safety net; can reduce perceived tail risk and potentially jump-start currency usage without frequent activation.
- Offshore clearing banks:
  - As of 2020: 27 offshore clearing banks in 25 economies.
  - Role: allow overseas institutions to settle RMB directly with local clearing banks, accumulate RMB liquidity, reduce time/cost and AML complications versus routing through domestic correspondent banks.
  - Since 2018: PBC granted RMB clearing licenses to foreign banks (examples: JP Morgan, MUFG Bank).
- CIPS (Cross-Border Interbank Payment System):
  - Potential to reduce role of offshore clearing banks by offering broader direct access to China’s domestic Large Payment Settlement System for RMB transactions.

### Empirical approach
- Dependent variables:
  - RMB usage measured as amount of RMB settlement in transactions with China.
  - RMB share in total cross-border transactions of economy i with China in period t.
  - Separate regressions for payments from China and payments to China.
- Key regressors and controls:
  - Lagged dependent variable (inertia).
  - Trade integration measures (China’s share in imports/exports/total trade).
  - Swap line dummy (outstanding swap line with PBC).
  - Clearing bank dummy (presence of local RMB clearing bank).
  - geographic_distance (log), political_distance (correlation of UN votes), contiguity indicator.
  - Other controls X: financial flows, inflation, income level, language, nominal GDP, per capita GDP, M2/GDP, inflation (logs).
- SWIFT message types:
  - Transfers: MT 103 and MT 202 (total = MT 103 + MT 202).
  - Trade-related: MT 400 and MT 700.

### Key empirical findings
- Persistence / inertia:
  - Lagged dependent variable coefficient reported ~0.8; regression ranges between 0.61 and 0.86 across specifications.
- Average policy impacts:
  - Swap lines could boost RMB payment growth by 0.4 percent on average.
  - Offshore clearing banks increase RMB payment growth by 0.5 percent on average.
  - 2021: average share of RMB payment in countries with swap lines and offshore clearing banks was 57 percent, versus 34 percent in other countries.
- Share-based regressions — transfers (MT 103 and MT 202):
  - Lagged coefficient ranges: 0.61 to 0.86 across OLS, fixed-effect, random-effect models.
  - Swap lines increased RMB share of payments to and from China by 2.2 to 3.7 percentage points (ppt), depending on specification.
  - Offshore clearing banks increased RMB share:
    - Payments to China: up to 6.7 percentage points.
    - Payments received from China: up to 3.9 percentage points.
  - Geographic distance: countries closer to China adopt RMB more frequently (distance coefficients negative and significant).
  - Political proximity: positive and statistically significant for transfers sent to China in some specifications.
  - Financial development: less-developed financial systems tend to settle a greater proportion of transactions with China in RMB (coefficient patterns reported).
- Trade-related payments (MT 400 and MT 700):
  - Policy impacts smaller relative to transfers:
    - Swap lines boost RMB share by 0.5 ppt.
    - Offshore clearing banks boost RMB share by 2.5 ppt.
  - Degree of trade integration important for RMB trade settlement shares.
- Third-party transactions: swap lines and offshore clearing banks have very limited impact on boosting RMB usage (noted in a footnote).

### Robustness and notable coefficient examples
- Lagged RMB payment share coefficients (selected):  
  - 0.740*** (0.0493); 0.744*** (0.0508); 0.478*** (0.0142); 0.471*** (0.0147); 0.745*** (0.0114); 0.656*** (0.0616); 0.570*** (0.0780); 0.377*** (0.0162); 0.309*** (0.0169); 0.327*** (0.0168).
- SWAP line indicator examples: 0.483** (0.208); 0.767*** (0.283); 0.861** (0.398); 0.761* (0.391).
- Offshore clearing examples: 2.262*** (0.461); 2.321*** (0.460); 0.719** (0.359); 1.143* (0.634); negative coefficients also reported: -0.480 (0.375); -1.517*** (0.516); -1.636*** (0.505); -1.676*** (0.495).
- Trade share examples: 0.375** (0.180); 0.218 (0.207); 1.203** (0.502); 1.346*** (0.520); 0.375** (0.172); 0.614*** (0.218); 0.589** (0.241).
- Geographic distance (log) examples: -0.459** (0.226); -0.407* (0.225); -0.341* (0.188); -1.102*** (0.308); -1.102*** (0.298); -3.977** (1.825).
- Political proximity (log) examples: 0.793 (1.036); 3.485 (3.812); -0.329 (1.351); 1.790 (1.561); 6.880 (4.776); 7.919* (4.390).
- Financial development examples: -0.393 (0.668); -0.673 (1.773); -0.215 (0.680); -0.511 (0.618); -3.750* (2.117); -3.142 (2.022).
- Model fit: R-squared examples: 0.570; 0.580; 0.277; 0.274; 0.574; 0.540; 0.391; 0.165; 0.118; 0.295. Observations examples: 4,099; 3,878; 3,369; 3,242; 3,242.
- Note: Robust standard errors in parentheses; significance: *** p<0.01, ** p<0.05, * p<0.1.

### Conclusion — implications and outlook
- Both bilateral swap lines and offshore clearing banks have positively facilitated RMB use in cross-border settlement, especially for transfers.
- Offshore RMB liquidity constraints—stemming from China’s capital account restrictions—hampered broader RMB use; policy measures expanding financial infrastructure improved access to RMB abroad.
- Currency usage shows strong inertia; geographic distance and geopolitical proximity matter materially.
- RMB adoption concentrated in Asia; expanding in parts of Latin America and Africa.
- Current global adoption described as "at infancy"; continued Chinese growth and global financial integration could see RMB play an increasingly important regional role over coming decades.

### Data sources and construction (key points)
- SWIFT BI Partnership data: MT_103 and MT_202 for total payments; MT_400 and MT_700 for trade-related payments. Raw monthly data consolidated to quarterly and annual frequency. Country-periods with no information on RMB usage filled with zero.
- Swap line and offshore clearing bank datasets: constructed from PBC’s annual reports on RMB internationalization.
- Trade data: IMF Direction of Trade Statistics (quarterly and annual); exports FOB; imports include insurance; values in USD using prevailing market exchange rates.
- GDP per capita: Quarterly and annual data from International Financial Statistics.
- Political proximity: UN voting patterns from Harvard Dataverse (correlation of UN voting).
- Geographic distance: GeoDist database of CEPII.

### Annex — Outstanding PBC Swap Lines (as of 2021)
- Albania Apr 2018 2
- Argentina Aug 2020 130
- Australia July 2021 200
- Belarus May 2018 7
- Canada Jan 2021 200
- Chile Aug 2021 50
- Egypt Feb 2020 18
- Euro Area Oct 2019 350
- Hong Kong SAR, China Nov 2020 500
- Hungary Dec 2019 60
- Iceland Oct 2020 3.5
- Indonesia Nov 2018 200
- Japan Oct 2018 200
- Kazakhstan May 2018 7
- Korea Oct 2020 400
- Lao P.D.R. May 2020 6
- Macao SAR, China Dec 2019 30
- Malaysia Nov 2021 180
- Mongolia Jul 2020 15
- New Zealand Aug 2020 25
- Nigeria Jun 2021 15
- Pakistan Jul 2021 30
- Qatar Jan 2021 35
- Russia Oct 2020 150
- Singapore 1/ May 2019 300
- South Africa Apr 2018 30
- Sri Lanka Jun 2021 10
- Suriname Feb 2019 1
- Switzerland Jul 2020 150
- Thailand Dec 2020 70
- Turkey Jun 2021 35
- United Kingdom Oct 2018 350
- Ukraine Dec 2018 15
- Note: Source: People's Bank of China. 1/ The swap line with Singapore was extended in July 2022.

*Source: wpiea2023077-print-pdf — Introduction, Conclusion, Annexes.*

### Introduction ...........................................................................................................

### Introduction

### Major themes and structure
- Introduction (page 3)
- Regional Patterns of RMB Cross-Border Payments (page 7)
- Regional Policies that Facilitate RMB Internationalization (page 9)
- Bilateral Swap Lines (page 9)
- Offshore Clearing Banks (page 11)
- Empirical Study (page 13)
- Conclusion (page 16)
- Annex I. Data Sources (page 17)
- Annex II. List of Swap Lines (page 18)
- References (page 19)

### Figures listed in this content unit
- Figure 1. China’s Rapid Integration vs. Limited Financial Integration
- Figure 2. Capital Account Openness by Income Level
- Figure 3. Evolution of RMB Cross-Border Payments
- Figure 4. Geographical Distribution of RMB Payments (2021)
- Figure 6. Outstanding Bilateral Swap Lines (2021)
- Figure 7. Example of Functioning of Central Bank Bilateral Swap Line
- Figure 8. RMB Offshore Clearing Banks

### Tables listed in this content unit
- Table 1. Roles of an International Currency
- Table 2. Regressions Results for Transfers (Messages MT 103 and MT 202)
- Table 3. Regressions Results for Trade-related Payments (Messages MT 400 and MT 700)

### Organizational notes relevant for indexing and ingestion
- The unit contains a dedicated Empirical Study section (page 13) and two regression result tables: Table 2 and Table 3.
- Policy and institutional mechanisms are covered in the sections titled Regional Policies that Facilitate RMB Internationalization (page 9), Bilateral Swap Lines (page 9), and Offshore Clearing Banks (page 11).
- Annexes include Data Sources (Annex I, page 17) and a List of Swap Lines (Annex II, page 18), which are likely to contain underlying data and enumerations referenced in the main text.

*Source: wpiea2023077-print-pdf - Introduction*

### Introduction

### wpiea2023077-print-pdf - Introduction

### Overview: China’s financial integration and RMB internationalization
- Over the past four decades China transformed into the second largest economy and "accounts for one-third of global growth (IMF, 2018)."
- China’s international assets and liabilities constitute only 4 percent of the world external assets and liabilities, compared to 13 percent in global trade.
- International use of RMB:
  - 2 percent of all global cross-border payments (based on Swift data).
  - 3 percent of central bank reserve assets (based on IMF COFFER dataset).
- China has maintained a closed capital account with strong capital account limits for decades; its capital mobility control is tighter than many peers.

### Timeline of RMB internationalization and policy actions
- Post-2008 Global Financial Crisis: PBC began promoting RMB internationalization.
  - 2009: PBC permitted cross-border settlements in RMB (initially pilots; nationwide since 2011).
  - PBC introduced bilateral swap lines and offshore clearing banks to facilitate RMB cross-border use.
  - 2015: RMB joined the basket of Special Drawing Rights.
  - Since 2017: Financial liberalization accelerated; RMB bonds included in major global indices.
- Structural payment infrastructure:
  - Offshore clearing banks established beginning in 2003 (first in Hong Kong SAR).
  - CIPS first phase completed in 2015; second phase completed in 2018. CIPS membership to date: 77 direct participants and 1283 indirect participants.

### Regional patterns and stylized facts (Swift-based evidence)
- Sample: Swift transaction currency usage covering a sample of 125 economies (data back to 2010).
- Evolution of RMB share in an economy’s total payments with China:
  - Median RMB usage increased from around 0 in 2014 to 20 percent in 2021.
  - 75th percentile increased from 0 into 70 percent in 2021.
  - 25th percentile remained close to zero in 2021.
- Geographic concentration (2021): RMB gained traction in Asian countries (e.g., Mongolia, Laos) and some emerging market and developing countries (e.g., Chile, Turkey, Argentina); countries subject to U.S. dollar sanctions (e.g., Iran) increasingly used RMB with China.

### Policy instruments to facilitate RMB use
- Bilateral swap lines (PBC):
  - Geographic coverage began with neighboring Asian countries, later expanded to other emerging markets and some advanced economies.
  - As of 2022: 38 bilateral swap lines outstanding, amounting to around 4 trillion RMB.
  - Typical term: three years, often renewed; some swap lines scaled up over time (e.g., Hong Kong SAR, Singapore, South Korea).
  - Actual activation has been limited: a 2015 report indicated about 100 billion of the 3 trillion RMB outstanding swaps were used in that year (less than 1 percent).
  - Swap lines serve as a safety net and can reduce perceived tail risk, potentially jump-starting currency usage even without frequent activation.
- Offshore clearing banks:
  - As of 2020: China established 27 offshore clearing banks in 25 economies.
  - Role: simplify settlement by allowing overseas institutions to settle RMB directly with local clearing banks, accumulate RMB liquidity, and reduce time/cost and AML complications relative to routing through domestic correspondent banks.
  - Since 2018: PBC began granting RMB clearing licenses to foreign banks (examples noted: JP Morgan, MUFG Bank).
- CIPS (Cross-Border Interbank Payment System):
  - Potential to reduce the role of offshore clearing banks as it offers broader direct access to China’s domestic Large Payment Settlement System for RMB transactions.

### Empirical approach: determinants of RMB cross-border payment usage
- Dependent variable: RMB usage measured two ways — amount of RMB settlement in transactions with China, and RMB share in total cross-border transactions of economy i with China in period t. Separate regressions for payments from China and payments to China.
- Key regressors and controls:
  - Lagged dependent variable to capture inertia; trade integration measures (China’s share in imports/exports/total trade); swap line dummy (outstanding swap line with PBC); clearing bank dummy (presence of local RMB clearing bank); geographic_distance (log), political_distance (correlation of UN votes), contiguity indicator; other controls X (financial flows, inflation, income level, language, etc.).
- Swift message types used:
  - Transfers: MT 103 (single customer fund transfers) and MT 202 (bank transfers); total payment = MT 103 + MT 202.
  - Trade-related: MT 400 (cash letters advice of payment) and MT 700 (confirmations of issuance of a trade documentary credit).

### Key empirical findings
- Persistence / inertia:
  - Lagged dependent variable coefficient ~0.8 (reported as 0.8 in text; regression ranges noted between 0.61 and 0.86 across specifications), indicating high persistence in currency usage.
- Policy impacts (average effects):
  - Establishment of swap lines could boost RMB payment growth by 0.4 percent on average.
  - Set-up of offshore clearing banks increases RMB payment growth by 0.5 percent on average.
  - 2021: average share of RMB payment in countries with swap lines and offshore clearing banks was 57 percent, compared to 34 percent in other countries.
- Regression (share-based) results — transfers (MT 103 and MT 202):
  - Lagged coefficient ranges between 0.61 and 0.86 across OLS, fixed-effect, and random-effect models.
  - Swap lines increased RMB share of payments to and from China between 2.2 and 3.7 percentage points (ppt), depending on specification.
  - Offshore clearing banks increased RMB share:
    - Payments to China by up to 6.7 percentage points.
    - Payments received from China by up to 3.9 percentage points.
  - Geographic distance: countries closer to China adopt RMB more frequently (geographic distance coefficients significant and negative).
  - Political proximity: positive and statistically significant effect on transfers sent to China in some specifications.
  - Financial development: evidence that countries with less developed financial systems settle a greater proportion of transactions with China in RMB (coefficient patterns reported).
- Trade-related payments (MT 400 and MT 700):
  - Impact of swap lines and offshore clearing banks is smaller in trade-related settlement:
    - Swap lines boost RMB share by 0.5 ppt.
    - Offshore clearing banks boost RMB share by 2.5 ppt.
  - Degree of trade integration becomes important in determining RMB trade settlement shares.

### Robustness and controls
- Robustness checks included GDP per capita, total GDP, financial depth (M2/GDP ratio), and inflation (in logs); coefficients of some controls are statistically significant but quantitatively small and often not stable across specifications.
- Policy variables (swap lines and offshore clearing banks) and geographic distance remain robust across model specifications.
- Results for RMB usage in third-party transactions show swap lines and offshore clearing banks have very limited impact on boosting RMB usage (noted in a footnote).

*Source: wpiea2023077-print-pdf - Introduction*

### Conclusion

### Conclusion — Renminbi Usage in Cross-Border Payments: Regional Patterns and the Role of Swap Lines and Offshore Clearing Banks

### Main findings
- The paper examines regional patterns of cross-border RMB payments using Swift data and identifies geographic heterogeneity in RMB usage.  
- Determinants explored include trade linkages, geographic distance, political proximity, and policy initiatives (bilateral swap lines between the PBC and foreign central banks, and offshore RMB clearing banks).  
- Both bilateral swap lines and offshore clearing banks have played a positive role in facilitating the use of RMB in cross-border settlement.  
- Offshore RMB liquidity is often constrained due to China’s overall capital account restrictions, which hampered broader RMB use; policy measures to boost financial infrastructures facilitated access to RMB in foreign countries and promoted its international usage.  
- There is significant inertia in currency usage for cross-border payments and an important role for non-economic variables such as geographic distance and geopolitical proximity.  
- RMB adoption is more pronounced in cross-border payments of Asian countries and is expanding in some parts of Latin America and Africa.  
- If China continues to grow and becomes more integrated into the global financial system, RMB can be expected to play an increasingly important role; current global adoption remains at infancy, but RMB might grow as a regional currency in the decades to come.

### Quantitative results (selected regression evidence)
- Lagged RMB payment share coefficients (various specifications):  
  - 0.740*** (0.0493)  
  - 0.744*** (0.0508)  
  - 0.478*** (0.0142)  
  - 0.471*** (0.0147)  
  - 0.745*** (0.0114)  
  - 0.656*** (0.0616)  
  - 0.570*** (0.0780)  
  - 0.377*** (0.0162)  
  - 0.309*** (0.0169)  
  - 0.327*** (0.0168)
- SWAP line indicator (coefficients and standard errors shown in table): examples include 0.483** (0.208), 0.767*** (0.283), 0.861** (0.398), 0.761* (0.391).
- Offshore clearing (coefficients): examples include 2.262*** (0.461), 2.321*** (0.460), 0.719** (0.359), 1.143* (0.634), and negative coefficients in other specifications: -0.480 (0.375), -1.517*** (0.516), -1.636*** (0.505), -1.676*** (0.495).
- Trade share (coefficients): 0.375** (0.180), 0.218 (0.207), 1.203** (0.502), 1.346*** (0.520), 0.375** (0.172), 0.614*** (0.218), 0.589** (0.241).
- Geographic distance (log): negative and significant coefficients reported, e.g., -0.459** (0.226), -0.407* (0.225), -0.341* (0.188), -1.102*** (0.308), -1.102*** (0.298), -3.977** (1.825).
- Political proximity (log): coefficients reported including 0.793 (1.036), 3.485 (3.812), -0.329 (1.351), 1.790 (1.561), 6.880 (4.776), 7.919* (4.390).
- Financial development: coefficients include -0.393 (0.668), -0.673 (1.773), -0.215 (0.680), -0.511 (0.618), -3.750* (2.117), -3.142 (2.022).
- Constants and model fit: R-squared values reported across specifications include 0.570, 0.580, 0.277, 0.274, 0.574, 0.540, 0.391, 0.165, 0.118, 0.295. Observations vary by specification (e.g., 4,099; 3,878; 3,369; 3,242; 3,242).
- Notes: Robust standard errors in parentheses; significance levels shown as *** p<0.01, ** p<0.05, * p<0.1. Economic control variables included: nominal GDP; per capita GDP; M2/GDP ratio; and inflation (all in logs). One observation equals the log of the share of trade-related amounts of CNY sent from/to China through SWIFT to/from other countries in a given quarter.

### Data sources and construction (key points)
- Swift messaging data under the ‘BI Partnership’ framework: MT_103 and MT_202 define total payment; MT_400 and MT_700 used for trade-related payments. Raw monthly data consolidated to quarterly and annual frequency. Country-periods with no information on RMB usage were filled with zero.  
- Swap line dataset and RMB offshoring clearing banks dataset constructed from PBC’s annual reports on RMB internationalization.  
- Trade data from IMF Direction of Trade Statistics (quarterly and annual); exports are FOB, imports include insurance; values denominated in USD using prevailing market exchange rates.  
- GDP per capita: Quarterly and annual data from the International Financial Statistics.  
- Political proximity: United Nations voting patterns from the Harvard Dataverse (degree of correlation of UN voting).  
- Geographic distance: GeoDist database of CEPII.

### Annex: Outstanding PBC Swap Lines (as of 2021) — counterpart, latest sign date, Amount (in bn RMB)
- Albania Apr 2018 2  
- Argentina Aug 2020 130  
- Australia July 2021 200  
- Belarus May 2018 7  
- Canada Jan 2021 200  
- Chile Aug 2021 50  
- Egypt Feb 2020 18  
- Euro Area Oct 2019 350  
- Hong Kong SAR, China Nov 2020 500  
- Hungary Dec 2019 60  
- Iceland Oct 2020 3.5  
- Indonesia Nov 2018 200  
- Japan Oct 2018 200  
- Kazakhstan May 2018 7  
- Korea Oct 2020 400  
- Lao P.D.R. May 2020 6  
- Macao SAR, China Dec 2019 30  
- Malaysia Nov 2021 180  
- Mongolia Jul 2020 15  
- New Zealand Aug 2020 25  
- Nigeria Jun 2021 15  
- Pakistan Jul 2021 30  
- Qatar Jan 2021 35  
- Russia Oct 2020 150  
- Singapore 1/ May 2019 300  
- South Africa Apr 2018 30  
- Sri Lanka Jun 2021 10  
- Suriname Feb 2019 1  
- Switzerland Jul 2020 150  
- Thailand Dec 2020 70  
- Turkey Jun 2021 35  
- United Kingdom Oct 2018 350  
- Ukraine Dec 2018 15  
- Note: Source: People's Bank of China. 1/ The swap line with Singapore was extended in July 2022.

*IMF Working Paper — Renminbi in Global Payments (Conclusion and Annexes).*

---


_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023077-print-pdf.pdf_